.png){kind=icon}
Return
Sonar-based robot navigation using nonlinear robust observers
.png){kind=icon}
PRE
AI
DOI：10.1016/S0005-1098(03)00089-X.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper addresses the sonar-based navigation of mobile robots. The extended Kalman filtering (EKF) technique is considered, but from a deterministic, nonstochastic, point of view. For this problem, new results are presented on the robustness of the nonlinear observation scheme. The original feature is that the region-of-convergence question is posed in its complete nonlinear framework, that is, considering the dynamics not only of the estimation error xi(t), but also of the covariance matrix P(t). In this way the approach followed makes less conservative the treatment and improves the convergence analysis. The proposed ideas were tested successfully on simulation experiments of a mobile platform. (C) 2003 Elsevier Science Ltd. All rights reserved.
Keywords:
nonlinear observers
extended Kalman filters (EKF)
robustness
sonar-based robot navigation
pose estimation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W
Organization
No organization information available
Cited Papers
ShareSaveThe Impact of Hybrid Quarantine Strategies and Delay factor on Viral Prevalence in Computer Networks
OAAI
OAAIShareSaveRelationship between polymer structure and gas transport properties in a series of fluorine-containing aromatic polyamide membranes for oxygen enrichment.png)
Desalination
DesalinationIF0
PREAI
ShareSaveShareSaveShareSaveShareSaveShareSaveShareSaveShareSave
View more